code: def create_keras_tensors(input_shape, dtype, sparse):
      if isinstance(input_shape, tuple):
          return KerasTensor(input_shape, dtype=dtype, sparse=sparse)
      if isinstance(input_shape, list):
          return [
              KerasTensor(s, dtype=dtype, sparse=sparse)
              for s in input_shape
          ]
      if isinstance(input_shape, dict):
          return {
              utils.removesuffix(k, "_shape"): KerasTensor(
                  v, dtype=dtype, sparse=sparse
              )
              for k, v in input_shape.items()
          }
      raise ValueError(
          f"Unsupported type for `input_shape`: {type(input_shape)}"
      )
  
imports: import json
  import shutil
  import tempfile
  import unittest
  import numpy
  import tree
  from keras import backend
  from keras import ops
  from keras import utils
  from keras.backend.common import is_float_dtype
  from keras.backend.common import standardize_dtype
  from keras.backend.common.global_state import clear_session
  from keras.backend.common.keras_tensor import KerasTensor
  from keras.models import Model
  from keras.utils import traceback_utils
label_desc: Use image node_id 1 for calling a global function with example usage: create_keras_tensors(input_shape, dtype, sparse) and returns: KerasTensor, unknown, unknown